Shu-Guang Wu

Spectral Graph Neural Networks with Hermite Polynomials: A Comprehensive Study

We study spectral graph neural networks built from Hermite polynomials and propose HermNet, a simple model that combines a nodewise predictor with normalized Hermite propagation. Its sparse recurrence requires neither eigendecomposition nor a learned basis. We distinguish the basic model from optional coordinate calibr...